feat: 模型评测端到端闭环 — EvalRunner引擎 + 算力节点Job执行 + 结果回写

算力节点 (compute):
- 新建 eval_runner.py: 评测执行引擎，作为subprocess运行
  - 加载模型 + JSONL数据集 + 逐样本推理
  - BLEU/ROUGE/Cosine基础指标计算
  - LLM Judge评分(OpenAI兼容API调用)
  - 结果写入eval_results.json
- adapter.py: build_command新增engine=eval分支
- main.py: 新增/json模块导入，新增/compute/files/read端点，eval job校验

后端:
- platform.py: 重写startEval提交eval job到算力节点
  - 支持models表和trained_models表查找
  - 已合并模型不传adapter路径
- platform_store.py: 新增update_eval_task/running_eval_tasks/apply_eval_job_result
- sync.py: poller新增eval job同步，异步读取eval_results.json回写结果

前端:
- EvalCreateView/DimensionCreateView: eval模型过滤扩展(API类型+api_url)
- EvalCreateView: GPU过滤在线节点空闲GPU
- EvalTaskSetupStep: GPU value从数组index改为gpu.id
- BasicMetricSetupStep: ROUGE方法名修正(rouge_1→rouge1)
- EvalView: 新增5秒轮询刷新

Co-Authored-By: Claude <noreply@anthropic.com>

frontend/src/views/eval/EvalCreateView.vue

@@ -11,6 +11,7 @@ import { createDimension, startEval } from '@/api/modules/eval'
 import { getTrainedModels, getModelList } from '@/api/modules/model'
 import { getDatasetList } from '@/api/modules/dataset'
 import { getSystemInfo } from '@/api/modules/system'
+import { getComputeNodes, type ComputeNode } from '@/api/modules/compute'
 import type { DatasetItem, Dimension, GpuInfo, ModelItem, TrainedModel } from '@/types'
 
 type StepExposed = { validate: () => Promise<boolean> }
@@ -84,15 +85,26 @@ async function loadData() {
     getDatasetList(),
     getSystemInfo(),
     getModelList(),
+    getComputeNodes(),
   ])
 
   if (results[0].status === 'fulfilled') trainedModels.value = results[0].value?.models || []
   if (results[1].status === 'fulfilled') {
     evalDatasets.value = (results[1].value || []).filter((dataset) => dataset.type === 'eval')
   }
-  if (results[2].status === 'fulfilled') gpus.value = results[2].value?.gpu || []
+  if (results[2].status === 'fulfilled') {
+    const allGpus: GpuInfo[] = results[2].value?.gpu || []
+    const nodes: ComputeNode[] = (results[4].status === 'fulfilled' ? results[4].value : []) || []
+    const onlineIds = new Set(nodes.filter((n) => n.enabled && n.scheduler_status === 'online').map((n) => n.id))
+    // Only show idle GPUs from online compute nodes
+    gpus.value = allGpus.filter(
+      (g) => g.status === 'idle' && (!g.node_id || onlineIds.has(g.node_id)),
+    )
+  }
   if (results[3].status === 'fulfilled') {
-    evalModels.value = (results[3].value || []).filter((model) => model.purpose === 'evaluation')
+    evalModels.value = (results[3].value || []).filter(
+      (model) => model.purpose === 'evaluation' || (model.model_source === 'api' && !!model.api_url),
+    )
   }
 
   const failedCount = results.filter((result) => result.status === 'rejected').length